A technique for the multiobjective optimisation of laminated composite structures using genetic algorithms and finite element analysis

Weight and deflection optimization of Cantilever Beam using a modified Non-Dominated sorting Genetic Algorithm

“…The fast sort algorithm [2] is given below:  For each individual p in main population P do the following Initialize S p = Ø. This set would contain all the individuals that arebeing dominated by p. Initialize n p = 0.…”

“…The comparison is carried out as below based on (1) Non-domination rank p rank , i.e., individuals in front F i will have their rank as p rank = i, and (2) [2,4] are used to create off-springs. The child population is then analyzed and ranked.…”

“…Amongst the several optimization methods there are a few which are more suitable for solving a multi-objective optimization problem with a large number of design variables and a relatively few number of constraints, which is the case in the structural topology optimization problem. Walker and Kumar have tackled complex multi-objective optimization problems by scalarising the multiple objective functions into a single objective using a weight vector [2,3]. A disadvantage of this approach is that the resulting optimal lamination scheme depends on the chosen weight vector.…”

Validation of the thin-walled composite box beams using FEM

“…Most of these works were restricted to the plate type structures [7][8][9][10][11][12] because of the mathematical complexity involved in the analysis of other composite structures. However, in recent year, the commercially available finite element software makes it possible to optimize the complicated composite structures [13][14][15]. For example, Kere et al [15] carried out the weight minimization of composite laminates by maximizing the strength for multiple loading conditions with number of layers and layer orientations as design variables.…”

Multi-objective design optimization of an innovative fibre composite sandwich panel for civil engineering applications

“…It was concluded that the maximum bending stiffness occurred at the core to skin weight ratio equal to 2.04. Walker and Smith (2003) presented multi-objective design optimization of fibre composite structure by using FE and genetic algorithms (GA). It was found that the weight and deflection as a multi-objective could be optimized by the GA to suite the design engineers requirements.…”